more amd tweaks

Signed-off-by: Lucas Wilkinson <[email protected]>

Author: LucasWilkinson

vllm/attention/backends/mla/common.py

@@ -196,6 +196,7 @@
 import torch
 
 from vllm import _custom_ops as ops
+from vllm import envs
 from vllm.attention.backends.abstract import (AttentionBackend, AttentionLayer,
                                               AttentionMetadata,
                                               AttentionMetadataBuilder,
@@ -215,6 +216,10 @@
 from vllm.utils import async_tensor_h2d, cdiv, make_tensor_with_pad, round_down
 from vllm.vllm_flash_attn.fa_utils import get_flash_attn_version
 
+if HAS_TRITON:
+    from vllm.attention.ops.triton_flash_attention import triton_attention
+else:
+    triton_attention = None
 
 try:
     from vllm.vllm_flash_attn import flash_attn_varlen_func
@@ -1039,6 +1044,7 @@ def __init__(
         self.kv_b_proj = kv_b_proj
         self.o_proj = o_proj
 
+        self.triton_fa_func = triton_attention
         # Handle the differences between the flash_attn_varlen from flash_attn
         # and the one from vllm_flash_attn. The former is used on RoCM and the
         # latter has an additional parameter to control FA2 vs FA3
@@ -1064,6 +1070,14 @@ def _flash_attn_varlen_diff_headdims(self, q, k, v, softmax_scale,
             maybe_padded_v = torch.nn.functional.pad(
                 v, [0, q.shape[-1] - v.shape[-1]], value=0)
 
+        if is_hip and envs.VLLM_USE_TRITON_FLASH_ATTN \
+            and not return_softmax_lse:
+            attn_out = self.triton_fa_func(
+                q,
+                k,
+                maybe_padded_v,
+                **kwargs,
+            )
         if is_vllm_fa:
             attn_out = self.flash_attn_varlen_func(
                 q=q,

vllm/v1/attention/backends/mla/common.py

@@ -195,7 +195,6 @@
 from vllm.attention.backends.abstract import (AttentionBackend, AttentionLayer,
                                               AttentionMetadata,
                                               MLAAttentionImpl)
-
 from vllm.attention.backends.utils import get_mla_dims
 from vllm.attention.ops.merge_attn_states import merge_attn_states
 from vllm.logger import init_logger
@@ -220,8 +219,6 @@
     from vllm.v1.worker.gpu_input_batch import InputBatch
     from vllm.v1.worker.gpu_model_runner import GPUModelRunner
 
-is_hip = current_platform.is_rocm()
-
 logger = init_logger(__name__)